Expansion for data processing of information within present corporate or enterprise environments requires an increase in processing cores, central processing units (CPUs), memory, and storage. However, as the need for more computing space and data rises, so does the cost of software deployed across the enterprise environment, since software licenses are based upon the number of cores, CPUs, and storage comprising the computing system upon which the software is installed. In particular, the total cost of ownership (TCO) is a financial estimate intended to help buyers and owners determine the direct and indirect costs of a product or system. It may include the costs of computer hardware and software, along with operational and long-term expenses. In particular, the computer hardware and software expenses may include the cost for the network (hardware and software), the server(s) (hardware and software), the workstation(s) (hardware and software), installation (hardware and software), purchasing research, warranties, licenses, license tracking and compliance, migration expenses, expenses associated with risk, support costs and the like.
As a solution to the proliferation of hardware, a converged infrastructure provides a solution for efficient use of resources, while minimizing infrastructure real estate and resources connected to networking, computing, and storage components. However, determining a configuration for a computing system upon with a software application is to be deployed can be a labor-intensive and complex task. Analyzing workloads, data volumes and systems to specify an appropriately sized computing system, such as a converged infrastructure computing system, to meet customer requirements (performance, scale, availability, capacity, and the like) is one of the steps in the architectural planning process. This analysis, however, is time consuming and tedious. Yet, computing system customers are increasingly sensitive to TCO with specific concerns surrounding software applications whose licensing costs are based upon the number of processors and/or processing cores. Accordingly, there exists a demand for a system and method for automatically determining a configuration for a proposed computing system upon which a software application will be deployed, which optimizes various parameters, such as TCO. It is within this context that the embodiments described below arise.